{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# n次伯努利实验"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x14c19cf1cd0>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "ans = [np.random.binomial(100, 0.5) for _ in range(1000)]\n",
    "plt.plot(ans)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "f4e85e907670104c152c8c682f7cbed26e7b3ec972bc4fb51086e49b6ea4cba4"
  },
  "kernelspec": {
   "display_name": "Python 3.8.12 64-bit (conda)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
